Service
AI Infrastructure & Architecture
The unglamorous layer that decides whether AI survives.
Retrieval you can trust, evaluations that run before release, observability, access control, and a cost line that stops surprising you.
What this is
Here is where production AI usually dies: retrieval nobody trusts, no evaluation, no record of what the system did or why, and a bill that arrives with no explanation. I build the layer that fixes all four — enterprise retrieval and knowledge systems, MCP servers, evaluation harnesses, an observability view leadership can read without a translator, data and access controls, and the caching and context engineering that take real money off the invoice. I’ve run the cloud infrastructure behind 17 production AI applications in a regulated industry and pushed vulnerability scanning across a portfolio of 30. Governance here isn’t paperwork. It’s what lets you say yes.
Why it’s worth a premium
I’ve been the person who signs for this. Every security vulnerability, policy, and remediation on a large healthcare cloud estate was mine to answer for, and cost auditing under me took 30–50% off the spend.
What you get
- Enterprise RAG and knowledge systems
- MCP servers and integrations
- Evaluation, observability, governance
- Cost control and spend visibility
How it fits the method
The AI Maturity Journey
AI Curiosity
Experiments
AI Automation
Copilots
Agentic Systems
Autonomy
AI-Native Organization
Leverage
Autonomous Enterprise
Compounding
The assessment takes about five minutes and gives you your stage, your real constraint, and the next move worth funding. If you’d rather talk it through, take thirty minutes with me. You’ll get a real answer either way, whether or not we end up working together.